In a data communication system, data is transmitted from a transmitter to a receiver. The implementation of the transmitter and receiver depends upon the channel over which the data is to be transmitted, e.g. whether the channel is wireless, a cable, or an optical fiber. Data transmitted over a channel is subject to degradation in transmission because of noise in the channel.
For example, in a data communication link over a fiber channel, the spectrum of the transmitted data signal may be cut due to the presence of optical or electrical components, such as wavelength selective switches (WSS's) or electrical drivers that do not accommodate the entire signal bandwidth. At an optical receiver, coherent detection may be performed, in which equalizers are used to mitigate channel impairments, e.g. optical impairments such as chromatic dispersion (CD) or polarization mode dispersion (PMD). In the case of dual polarization optical transmission, the impairments may be mitigated using a linear equalizer implemented as a 2×2 butterfly multiple-input multiple-output (MIMO) structure. In the context of a wireless channel, a receiver may try to remedy signal degradations associated with wireless channel specific conditions such as fading.
Although the linear equalizer in the receiver may mitigate the effect of inter-symbol interference (ISI) associated with the use of narrowband filters by band-limiting components in the optical-electrical or electrical-electrical path, the equalizer may also result in the amplification and coloring of noise. This is a common issue in any linear equalizer. Either or both of the amplification and the coloring of noise, in turn, may significantly degrade the bit-error-rate (BER) performance of the system.
Possible solutions include increasing the signal-to-noise ratio (SNR) and/or increasing the complexity of equalization by further processing of the output of the linear equalizer (2×2 MIMO) using a second post-compensation stage at the receiver in order to try to reduce the BER before the forward error correction (FEC) decoding to try to achieve zero post-FEC BER. However, increasing the SNR typically results in more power consumption at the transmitter side, and in some scenarios may lead to non-linear channel distortion. On the other hand, increasing the complexity of the equalization with a post-compensation stage at the receiver adds complexity, which typically increases power consumption and required implementation resources and may also add delay in decoding of the data in the received signal.